CN113607765A - Pollution source searching method based on poor products in semiconductor production line - Google Patents
Pollution source searching method based on poor products in semiconductor production line Download PDFInfo
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Abstract
The invention discloses a method for searching a pollution source based on a defective product in a semiconductor production line, which comprises the following steps: (1) firstly, judging whether the bad reason is caused by a machine associated with a bad product or caused by the environment, and if the bad reason is caused by the machine associated with the bad product, carrying out the next step; (2) determining the species of the contaminant; (3) the equipment comprises a machine station for examining the machine station in the clean room space to be monitored and eliminating the pollutant species which are not related; (4) reverse backward thrust is carried out by utilizing the airflow streamline, and machines which cannot be passed by the airflow streamline are removed from machines which are associated with defective products; (5) finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines; (6) further testing determines the source of the contaminant. The method of the invention not only does not increase extra investment and has lower cost, but also can effectively search the pollution source, thereby forming a set of systematic method.
Description
Technical Field
The invention relates to the technical field of semiconductors, in particular to a pollution source searching method based on poor products in a semiconductor production line.
Background
The semiconductor Integrated Circuit (IC) industry has experienced exponential growth, and technological advances in IC materials and design have resulted in generations of ICs where each generation has smaller and more complex circuits than the previous generation. During IC development, functional density has increased substantially while geometry has decreased. Generally, such a scaling down process provides many benefits by increasing production efficiency and reducing associated costs. This scaling down increases the complexity of processing and producing ICs and also places increasing demands on the production environment (clean room). In particular, in order to further scale down geometries, gaseous molecular contamination (AMC) is becoming an increasingly serious problem in semiconductor manufacturing processes.
The clean room is a space with better tightness, which can control the parameters of air cleanliness, temperature, humidity, pressure, noise and the like according to requirements. It has been counted in China that the qualification rate of producing MOS circuit tube cores under the environment without the requirement of clean grade is only 10% -15%, and the 64-bit storage is only 2%. Therefore, it is now common to use clean rooms in precision machinery, semiconductor, aerospace, atomic energy, and other industries. The clean room in the prior art comprises a clean space, a ceiling and an elevated floor, wherein a plurality of air supply areas are arranged on the ceiling, each air supply area comprises at least one air supply mechanism, the elevated floor is provided with a plurality of air exhaust areas, the air supply mechanism is an FFU (fan filter unit) device (or comprises the FFU device and a chemical filter), the FFU device is used for supplying air and filtering larger particle pollutants, and the chemical filter is used for filtering corrosive gas.
As mentioned above, in the semiconductor manufacturing process, the products are mounted on a wafer FOUP (FOUP), suspended on an overhead track, and sent to different machines for processing according to a work order, which is often hundreds of times; the specific operation is as follows: a FOUP (typically, 25 pieces) is transferred to a designated tool and then is put down from the air, at which time a door on one side of the FOUP is opened by the tool, but after the FOUP is opened, only one tool can be grabbed at a time, and at which time the FOUP is left inside, the FOUP is contaminated (for example, when a contaminated gas exists in the environment, the wafers inside the FOUP are contaminated); similarly, the produced semiconductor products (also referred to as semi-finished products) are returned to the FOUP, where the finished semiconductor products are also left unprocessed, and where they are contaminated. Therefore, in the prior art, the AMC concentration in the clean room needs to be maintained below a predetermined level, so as to ensure the normal process and the yield of the product.
However, the existing clean room usually includes a huge number of machines, which often become the generation place of the contamination source, and once one of the machines leaks, it will not only contaminate the process and FOUP (including the semi-finished product inside the FOUP) but also contaminate the whole clean space with the flowing of the air flow, thereby causing a fatal influence on the semiconductor production line in the whole clean space. Therefore, how to monitor these machines and find the machines generating pollution in time is a technical problem that is always difficult to solve in the field.
Aiming at the problems, in the prior art, the whole semiconductor production line is artificially divided into a plurality of working procedures, the yield of semiconductor products is detected every other one or more working procedures, once defects are found, the semiconductor products are immediately returned to search for a pollution source, so that the source of the pollution source can be immediately determined, and then maintenance or management and control are immediately carried out to prevent the pollution sources from diffusing. However, in the actual operation process, the following are found: (1) if the machine station where the defective products are located has problems, the problem is well solved, namely the machine station is maintained; (2) if the manufacturing technology has problems, the improvement can be carried out by technical personnel; (3) however, if the pollution is caused by the environment (i.e. the pollution caused by other machines in the clean space), the skilled person can not do so.
Therefore, in order to solve the above problems, it is obvious that the method for searching for the pollution source based on the bad products in the semiconductor production line has positive practical significance.
Disclosure of Invention
The invention aims to provide a pollution source searching method based on a poor product in a semiconductor production line.
In order to achieve the purpose, the invention adopts the technical scheme that: a method for searching pollution sources based on defective products in a semiconductor production line is disclosed, wherein the semiconductor production line is positioned in a clean room to be monitored, the semiconductor production line comprises a plurality of working procedures, and the yield of the semiconductor products is detected every other working procedure or every few working procedures; the method comprises the following steps:
(1) when a semiconductor product is detected to be defective in a certain yield detection process, firstly, judging whether the defective reason is caused by a machine associated with a defective product or caused by the environment, if so, maintaining the machine, and if not, performing the next step;
(2) determining the species of the contaminant;
(3) inspecting machines in the clean room space to be monitored, and removing machines which do not generate pollutant species related to the step (2);
(4) performing computational fluid dynamics simulation on the airflow in the clean room space to be monitored to obtain an airflow streamline from an outlet of the fan filtering unit to an inlet of the fan filtering unit in the clean room space to be monitored;
reverse backward thrust is carried out by utilizing the airflow streamline, and machines which cannot be passed by the airflow streamline are removed from machines which are associated with defective products;
(5) finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines;
(6) then, further detecting the machine station after the step is eliminated by adopting movable detection equipment, so that the source of the pollutant can be determined;
the number of the machines in the clean room space to be monitored is more than or equal to 100.
In the above, the "machine associated with the defective product" in the step (1) refers to: when a defect occurs, the machine where the defective product is located and the machine contacted in several production processes before the yield detection process. The "several production steps before this yield detection step" means: the semiconductor production line includes a plurality of processes, and the semiconductor product is subjected to yield detection every one or more processes, so that there are several production processes before the yield detection, for example: the production process and yield detection of the semiconductor production line are as follows: p1, P2, T1, P3, P4, P5, T2, P6, P7, T3, P8, P9, P10, T4 and P11 …, wherein P1 to P11 are production processes 1 to 11, and T1 to T4 are yield detection processes 1 to 4; when the T3 detects the defect of the semiconductor product, the "several production processes before the yield detection process" refer to the P6 and P7 processes. The "machine that is touched in the production processes before the yield inspection process" refers to a machine to which the FOUP is dispatched in the P6 and P7 processes.
In the above, the number of machines in the clean room space to be monitored is greater than or equal to 100, preferably, the number of machines is greater than or equal to 300, more preferably 500, and more preferably 1000.
In the above, between the step (2) and the step (3), there is further the step (2a) as follows: and judging whether the source of the pollutant is external air or not by using an AMC (automatic modulation and coding) online monitoring system, if so, correcting the external air, and if not, carrying out the next step.
In the above, Computational Fluid Dynamics, CFD, is known in English as Computational Fluid Dynamics. Preferably, in the step (2), the contaminant species include HF, HCl, Cl2、NH3、NOx、SO2、H2S, acetic acid and TVOC.
The semiconductor production line is positioned in a clean room to be monitored, and comprises a plurality of working procedures, wherein the yield of the semiconductor product is detected every other working procedure or working procedures; the method comprises the following steps:
(1) when a semiconductor product is detected to be defective in a certain yield detection process, firstly, judging whether the defective reason is caused by a machine associated with a defective product or caused by the environment, if so, maintaining the machine, and if not, performing the next step;
(2) determining the species of the contaminant;
(3) inspecting machines in the clean room space to be monitored, and removing machines which do not generate pollutant species related to the step (2);
(4) performing computational fluid dynamics simulation on the airflow in the clean room space to be monitored to obtain an airflow streamline from an outlet of the fan filtering unit to an inlet of the fan filtering unit in the clean room space to be monitored;
reverse backward thrust is carried out by utilizing the airflow streamline, and machines which cannot be passed by the airflow streamline are removed from machines which are associated with defective products;
(5) finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines;
(6) then, a movable sampling device is adopted to further sample the pollutant sources eliminated in the steps, and then further detection is carried out, so that the sources of the pollutants can be determined;
the number of the machines in the clean room space to be monitored is more than or equal to 100.
In the above, the number of machines in the clean room space to be monitored is greater than or equal to 100, preferably, the number of machines is greater than or equal to 300, more preferably 500, and more preferably 1000.
In the above, between the step (2) and the step (3), there is further the step (2a) as follows: and judging whether the source of the pollutant is external air or not by using an AMC (automatic modulation and coding) online monitoring system, if so, correcting the external air, and if not, carrying out the next step.
In the above, Computational Fluid Dynamics, CFD, is known in English as Computational Fluid Dynamics. Preferably, in the step (2), the contaminant species include HF, HCl, Cl2、NH3、NOx、SO2、H2S, acetic acid and TVOC.
Preferably, between the steps (4) and (5), the following step (4a) is further provided: and (4) matching the characteristics of the machine according to the occurrence rule of the defective products, and eliminating the machine which is impossible.
Preferably, in the step (4a), the occurrence rule of the defective products includes the following three rules: (A) continuously generating the bad effect from a certain time, (B) only occurring in a burst mode, (C) periodically generating the bad effect;
the machine characteristics include the following three types: (A) continuous operation from a certain time, (B) only once in a while, (C) periodic operation;
and when the occurrence rule of the defective products is the same as the machine characteristics, judging the machine to be a suspicious machine, otherwise, judging the machine to be an impossible machine.
Preferably, in the step (4), the computational fluid dynamics simulation of the airflow and the airflow streamline are completed before the step (1). Namely: the flow streamlines may also be made initially.
Preferably, the semiconductor production line comprises 20 to 3000 processes. This is prior art; at present, the existing semiconductor production line generally has 100-2000 processes, and there are more and less, and the number is determined by the trial product, and the processes may be more and more in the future, and exceed 3000.
Preferably, the semiconductor product is subjected to yield detection every 1-10 processes. The yield detection is performed every other number of processes, which is determined by the skilled in the art according to the actual situation, and may be 1 to 3 processes, or 5 to 8 processes, and this is not limited here.
Preferably, in the step (4), reverse thrust is performed by using the airflow streamline, and from the machine station associated with the defective product, the machine station passes through the outlet of the fan filtering unit, the inlet of the fan filtering unit, the return air channel and other machine stations on the airflow streamline in sequence, and the machine station which cannot be passed through by the airflow streamline is removed.
Preferably, in the step (5), the impossible tools are detected according to the time characteristic of the reversed airflow streamline and the start time of the tools, and then the impossible tools are excluded, specifically as follows:
te-ts is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein ts refers to the time point when the suspicious machine starts to operate, te refers to the time point when the suspicious machine finishes operating, and T refers to the time from the machine with the bad airflow streamline to the suspicious machine;
or T-te is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein: t is the time point when the machine is bad, and te is the time point when the suspicious machine finishes running; and T refers to the time from the machine with the bad occurrence to the suspicious machine of the airflow streamline.
Preferably, in step (2), one or more of the following detection methods are used to determine the species SEM, FIB, FTIR and EDS of the contaminant.
SEM, scanning electron microscope, provides images of high resolution and long depth of field for the sample surface and near surface. SEM is currently one of the most widely used analytical tools, due to the ability to provide detailed images quickly. FIB, focused ion beam, sample modification using well focused ion beam and image acquisition. FIB mainly takes very precise sample cross-section or performs circuit modification after SEM, STEM, TEM imaging. Fourier transform infrared spectroscopy (FTIR) test: FTIR technology can be used to detect a variety of different chemical molecules and has a relatively high discrimination rate for the simultaneous presence of different chemical species. EDS is energy spectroscopy.
Due to the application of the technical scheme, compared with the prior art, the invention has the following advantages:
1. the invention develops a new method for searching pollution sources based on bad products in a semiconductor production line, which comprises the steps of sequentially removing a part of machines through the species of pollutants, reversely pushing through an airflow streamline to remove a part of machines, and removing a part of machines through the time characteristic of the reverse airflow streamline and the initial time of the machines, so that thousands of machines are screened to the number of machines with extremely small number (such as within single digit), and detection objects are greatly reduced; then further precise detection is carried out, and finally the source of the pollutant is determined; therefore, the method of the invention not only does not increase extra investment and has lower cost, but also can effectively search the pollution source, thereby forming a set of systematic method, solving the technical problems which need to be solved urgently but are not solved all the time in the field, and obviously having positive practical significance;
2. according to the pollution source searching method, the airflow is utilized to carry out computational fluid dynamics simulation to obtain the airflow streamline, then the airflow streamline is utilized to carry out reverse thrust, and the machines which are associated with the defective products are discharged by sequentially passing through the outlet of the fan filtering unit, the inlet of the fan filtering unit, the return air channel and other machines on the airflow streamline, so that which machines are not associated with the airflow streamline can be quickly and accurately judged, and therefore, the efficiency is high, and the cost is low;
3. in the step (5), according to the time characteristic of the reverse airflow streamline and the initial time of the machine, the inconsistent machine is eliminated, the screening quantity is further reduced, and a solid foundation is laid for the feasibility of the whole set of scheme;
4. according to the invention, the characteristics of the machine are matched according to the occurrence rule of the defective products, the impossible machine is eliminated, the screening quantity is further reduced, and a solid foundation is laid for the feasibility of the whole set of scheme;
5. the detection method is simple and easy to implement, low in cost and suitable for popularization and application.
Drawings
Fig. 1 is a schematic diagram illustrating a defective product continuously generating defects from a certain time according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a defective product appearing only once in a burst mode according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a periodic defect of a defective product according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of reverse thrust of airflow streamlines in accordance with an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings and examples:
example one
Referring to fig. 1 to 4, a method for searching a pollution source based on a defective product in a semiconductor production line, wherein the semiconductor production line is located in a clean room to be monitored, the semiconductor production line comprises 1200 processes, and the yield of the semiconductor product is detected every 5 processes; the method comprises the following steps:
(1) when a semiconductor product is detected to be defective in a certain yield detection process, firstly, judging whether the defective reason is caused by a machine associated with a defective product or caused by the environment, if so, maintaining the machine, and if not, performing the next step;
(2) determining the species of the contaminant; using SEM, EDS and FIB to determine the species of the contaminant;
(3) inspecting machines in the clean room space to be monitored, and removing machines which do not generate pollutant species related to the step (2);
(4) performing computational fluid dynamics simulation on the airflow in the clean room space to be monitored to obtain an airflow streamline from an outlet of the fan filtering unit to an inlet of the fan filtering unit in the clean room space to be monitored;
the airflow streamline is utilized to carry out reverse thrust, and the machine stations which are associated with defective products are sequentially passed through the outlet of the fan filtering unit, the inlet of the fan filtering unit, the return air channel and other machine stations on the airflow streamline, so that the machine stations which cannot be passed through by the airflow streamline are removed; referring now to FIG. 4: A. b is two machines, namely FOUP is arranged beside the machine A, the product is polluted in the FOUP, all the airflow streamlines passing through the machine A are checked from the machine A, and other machines (such as the machine B) passing through the airflow streamlines are searched by reverse deduction;
(4a) the method comprises the following steps According to the appearance rule cooperation board characteristic of defective products, get rid of the board that is impossible, specifically as follows: the appearance rule of the defective products comprises the following three types: (A) continuously generating the defects from a certain time (see figure 1), (B) only generating the defects in a burst mode (see figure 2), (C) periodically generating the defects (see figure 3);
the machine characteristics include the following three types: (A) continuous operation from a certain time, (B) only once in a while, (C) periodic operation;
when the occurrence rule of the defective products is the same as the machine characteristics, the machine is judged to be a suspicious machine, otherwise, the machine is an impossible machine; (impossible machine is the machine excluded)
(5) Finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines;
(6) and then, further detecting the machine station after the step is eliminated by adopting movable detection equipment, so that the source of the pollutant can be determined.
In this embodiment, in the step (5), the impossible tools are found out according to the time characteristic of the reversed airflow streamline and the initial time of the tools, and then the impossible tools are excluded, specifically as follows:
te-ts is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein ts refers to the time point when the suspicious machine starts to operate, te refers to the time point when the suspicious machine finishes operating, and T refers to the time from the machine with the bad airflow streamline to the suspicious machine; or T-te is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein: t is the time point when the machine is bad, and te is the time point when the suspicious machine finishes running; and T refers to the time from the machine with the bad occurrence to the suspicious machine of the airflow streamline.
Example two
A method for searching for a pollution source based on a bad product in a semiconductor production line has the same steps as the first embodiment, and the only difference is that: in the step (5), the movable sampling device is adopted to further sample the pollutant sources removed in the previous step respectively, and then further detection is carried out, so that the sources of the pollutants can be determined.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for searching pollution sources based on defective products in a semiconductor production line is disclosed, wherein the semiconductor production line is positioned in a clean room to be monitored, the semiconductor production line comprises a plurality of working procedures, and the yield of the semiconductor products is detected every other working procedure or every few working procedures; the method is characterized by comprising the following steps:
(1) when a semiconductor product is detected to be defective in a certain yield detection process, firstly, judging whether the defective reason is caused by a machine associated with a defective product or caused by the environment, if so, maintaining the machine, and if not, performing the next step;
(2) determining the species of the contaminant;
(3) inspecting machines in the clean room space to be monitored, and removing machines which do not generate pollutant species related to the step (2);
(4) performing computational fluid dynamics simulation on the airflow in the clean room space to be monitored to obtain an airflow streamline from an outlet of the fan filtering unit to an inlet of the fan filtering unit in the clean room space to be monitored;
reverse backward thrust is carried out by utilizing the airflow streamline, and machines which cannot be passed by the airflow streamline are removed from machines which are associated with defective products;
(5) finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines;
(6) then, further detecting the machine station after the step is eliminated by adopting movable detection equipment, so that the source of the pollutant can be determined;
the number of the machines in the clean room space to be monitored is more than or equal to 100.
2. A method for searching pollution sources based on defective products in a semiconductor production line is disclosed, wherein the semiconductor production line is positioned in a clean room to be monitored, the semiconductor production line comprises a plurality of working procedures, and the yield of the semiconductor products is detected every other working procedure or every few working procedures; the method is characterized by comprising the following steps:
(1) when a semiconductor product is detected to be defective in a certain yield detection process, firstly, judging whether the defective reason is caused by a machine associated with a defective product or caused by the environment, if so, maintaining the machine, and if not, performing the next step;
(2) determining the species of the contaminant;
(3) inspecting machines in the clean room space to be monitored, and removing machines which do not generate pollutant species related to the step (2);
(4) performing computational fluid dynamics simulation on the airflow in the clean room space to be monitored to obtain an airflow streamline from an outlet of the fan filtering unit to an inlet of the fan filtering unit in the clean room space to be monitored;
reverse backward thrust is carried out by utilizing the airflow streamline, and machines which cannot be passed by the airflow streamline are removed from machines which are associated with defective products;
(5) finding out impossible machines according to the time characteristic of the reverse airflow streamline and the initial time of the machines, and then removing the impossible machines;
(6) then, a movable sampling device is adopted to further sample the pollutant sources eliminated in the steps, and then further detection is carried out, so that the sources of the pollutants can be determined;
the number of the machines in the clean room space to be monitored is more than or equal to 100.
3. The method according to claim 1 or 2, characterized in that, between the steps (4) and (5), there is further provided a step (4a) of: and (4) matching the characteristics of the machine according to the occurrence rule of the defective products, and eliminating the machine which is impossible.
4. The method of claim 3, wherein in the step (4a), the occurrence rule of the defective products comprises the following three rules: (A) continuously generating the bad effect from a certain time, (B) only occurring in a burst mode, (C) periodically generating the bad effect;
the machine characteristics include the following three types: (A) continuous operation from a certain time, (B) only once in a while, (C) periodic operation;
and when the occurrence rule of the defective products is the same as the machine characteristics, judging the machine to be a suspicious machine, otherwise, judging the machine to be an impossible machine.
5. The method according to claim 1 or 2, wherein in step (4) the computational fluid dynamics simulation of the gas flow and the gas flow streamlines are completed before step (1).
6. The method according to claim 1 or 2, wherein the semiconductor production line comprises 20 to 3000 processes.
7. The method of claim 1 or 2, wherein the semiconductor product is tested for yield rate every 1-10 processes.
8. The method as claimed in claim 1 or 2, wherein in the step (4), the reverse thrust is performed by using the airflow streamline, and the machine stations associated with the defective products pass through the outlet of the fan filtering unit, the inlet of the fan filtering unit, the return air channel and other machine stations on the airflow streamline in sequence, so as to remove the machine stations which the airflow streamline cannot pass through.
9. The method according to claim 1 or 2, wherein in the step (5), the impossible tools are detected according to the time characteristic of the reversed flow line and the start time of the tool, and then the impossible tools are excluded, specifically as follows:
te-ts is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein ts refers to the time point when the suspicious machine starts to operate, te refers to the time point when the suspicious machine finishes operating, and T refers to the time from the machine with the bad airflow streamline to the suspicious machine;
or T-te is more than or equal to T, which indicates that the machine is the source of the pollutant, otherwise, the machine is removed; wherein: t is the time point when the machine is bad, and te is the time point when the suspicious machine finishes running; and T refers to the time from the machine with the bad occurrence to the suspicious machine of the airflow streamline.
10. The method of claim 1 or 2, wherein in step (2) the species of contaminant is determined using one or more of the following detection methods: SEM, FIB, FTIR, EDS.
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